Currently, I think we are experiencing the same issues we experienced with all the new things we learned during the software engineering learning journey. When something new is learned, it tends to be abused and used as the solution for all potential problems, even when it is not needed or when those problems could be solved much better with older solutions. I feel like now, when someone faces a problem, the focus and flow of thinking is not “How can I solve this problem?” Instead, it’s “Hmm, which skills could I make and use to solve this problem? Can I maybe finally use some subagents, or maybe more of them, or something like that?” Just to show mastery and a wide spectrum of learned AI skills. It maybe reminds me of university when I had just learned some design patterns, and then for each problem I tried to use as many of them as possible. Similar thinking pattern: instead of thinking about how to solve a problem, I thought about where I could use a Singleton during problem solving. Don’t get me wrong, Claude Code and other coding agents are great things and definitely can make life and coding much easier. At least they can make coding faster so we can focus on the real problem. But using them when they are not needed, or for things that do not require any AI reasoning and are not even that complex, can make the overall workflow much worse. Sometimes we even introduce non deterministic behavior into places where a simple deterministic solution would have been more than enough. What are your thoughts and experiences? Do you feel the same, or have you seen different patterns emerging? Have you found yourself reaching for agents and complex workflows when a simpler solution would have been enough, or when the problem could have been solved just as effectively without them? submitted by /u/worksfinelocally
Originally posted by u/worksfinelocally on r/ClaudeCode